Title |
A method for increasing expressivity of Gene Ontology annotations using a compositional approach
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Published in |
BMC Bioinformatics, May 2014
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DOI | 10.1186/1471-2105-15-155 |
Pubmed ID | |
Authors |
Rachael P Huntley, Midori A Harris, Yasmin Alam-Faruque, Judith A Blake, Seth Carbon, Heiko Dietze, Emily C Dimmer, Rebecca E Foulger, David P Hill, Varsha K Khodiyar, Antonia Lock, Jane Lomax, Ruth C Lovering, Prudence Mutowo-Meullenet, Tony Sawford, Kimberly Van Auken, Valerie Wood, Christopher J Mungall |
Abstract |
The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 20% |
United Kingdom | 2 | 13% |
Switzerland | 1 | 7% |
Norway | 1 | 7% |
Sweden | 1 | 7% |
Japan | 1 | 7% |
Mexico | 1 | 7% |
Unknown | 5 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 8 | 53% |
Members of the public | 6 | 40% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 5% |
United Kingdom | 2 | 2% |
Netherlands | 1 | 1% |
Colombia | 1 | 1% |
Germany | 1 | 1% |
France | 1 | 1% |
Unknown | 75 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 28% |
Student > Ph. D. Student | 18 | 21% |
Student > Master | 10 | 12% |
Student > Doctoral Student | 6 | 7% |
Student > Bachelor | 5 | 6% |
Other | 12 | 14% |
Unknown | 10 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 28 | 33% |
Computer Science | 17 | 20% |
Biochemistry, Genetics and Molecular Biology | 15 | 18% |
Medicine and Dentistry | 5 | 6% |
Engineering | 4 | 5% |
Other | 7 | 8% |
Unknown | 9 | 11% |